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Ligand selectivity and competition between enzymes in silico

Nature Biotechnology volume 22, pages 1039–1045 (2004)Cite this article

Abstract

In a cell, there are many possibilities for cross interactions between enzymes and small molecules, arising from the similarities in the structures of the metabolites and the flexibility in binding of protein active sites. Despite this promiscuity, the cognate partners must be able to recognize each other in vivo, for the cell to function efficiently. This study examines the basis of this selectivity in recognition using standard docking calculations and finds significant improvement when proteins and ligands are cross-docked. We find that cognate molecules rarely form the most stable complexes and that specificity may be driven either by recognition of the substrate by the enzyme or the recognition of the enzyme by the substrate. Despite limitations of the in silico methods, especially the scoring functions, these calculations highlight the need to consider cross reactions in the cell and suggest that localization and compartmentalization must be important factors in the evolution of complex cells. However, the inherent promiscuity of these interactions can also benefit an organism, by facilitating the evolution of new functions from old ones. The results also suggest that high-throughput screening should involve not just a panel of small molecules, but also a panel of proteins to test for cross-reactivity.

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Figure 1: Structural diversity of the substrates in this study.
Figure 2: Binding energy distributions for the best-docked complexes.
Figure 3: Distribution of ranks for cognate complexes.
Figure 4: Enzyme versus substrate specificity.
Figure 5: P value correlations with r.m.s.d. and substrate volume.
Figure 6: Variation of P values with ligand and binding site volume.

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Acknowledgements

We wish to thank Tim Massingham for advice on the statistics in this study, Jonathan Barker for help with creating Figure 6, and John Mitchell, Robert Glen and Hannes Ponstingl for useful discussions. A.M. visited the European Bioinformatics Institute with a Marie Curie Training Site Fellowship of the European Commission Program 'Quality of Life,' contract number: QLRI-1999-50595. I.N. acknowledges financial support from the Medical Research Council, in the form of a Special Training Fellowship in Bioinformatics.

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  1. Antonio Macchiarulo

    Present address: Dipartimento di Chimica e Tecnologia del Farmaco, Università di Perugia, via del Liceo 1, 06127, Perugia, Italy

Authors and Affiliations

  1. EMBL-European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, CB10 1SD, Cambridge, UK

    Antonio Macchiarulo, Irene Nobeli & Janet M Thornton

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  1. Antonio Macchiarulo
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  2. Irene Nobeli
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Correspondence to Janet M Thornton.

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Supplementary information

Supplementary Fig. 1

Docked solutions with rmsd greater than 3 Å (PDF 309 kb)

Supplementary Table 1

The data set of 29 complexes with known protein crystal structures (PDF 46 kb)

Supplementary Table 2

List of enzymes and metabolites used in this study (PDF 9 kb)

Supplementary Methods (PDF 6 kb)

Supplementary Notes (PDF 14 kb)

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Macchiarulo, A., Nobeli, I. & Thornton, J. Ligand selectivity and competition between enzymes in silico. Nat Biotechnol 22, 1039–1045 (2004). https://doi.org/10.1038/nbt999

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